Compacting dispersed storage space

ABSTRACT

A method includes a storage unit receiving an encoded data slice for storage in memory that is organized as log files. The method further includes the storage unit identifying a first log file of the log files for storing the encoded data slice based on one or more of: the first DSN virtual address and the first size information. The method further includes the storage unit comparing storage parameters of the first log file with desired storage parameters associated with the encoded data slice. When the storage parameters of the identified log file compare unfavorably with the desired storage parameters, the storage unit identifies a second log file, stores the encoded data slice in the second log file, and updates a slice location table.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No.13/270,528 entitled “COMPACTING DISPERSED STORAGE SPACE”, filed Oct. 11,2011, which claims priority pursuant to 35 U.S.C. § 119(e) to U.S.Provisional Patent Application No. 61/408,980 entitled, “DISPERSEDSTORAGE NETWORK COMMUNICATION,” filed Nov. 1, 2010, expired, both ofwhich are incorporated herein by reference in their entirety and madepart of the present U.S. Utility Patent Application for all purposes.

U.S. Utility patent application Ser. No. 13/270,528 also claims priorityunder 35 U.S.C. § 120 as a continuation-in-part (CIP) of U.S. Utilitypatent application Ser. No. 12/983,232, entitled “DISTRIBUTEDLY STORINGRAID DATA IN A RAID MEMORY AND A DISPERSED STORAGE NETWORK MEMORY,”filed Dec. 31, 2010, issued as U.S. Pat. No. 8,725,940 on May 13, 2014,which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. ProvisionalApplication No. 61/308,938, entitled “MULTIPLE MEMORY TYPE STORAGESYSTEM,” filed Feb. 27, 2010, expired, and U.S. Provisional ApplicationNo. 61/314,166, entitled “STORAGE AND RETRIEVAL INA DISTRIBUTED STORAGESYSTEM”, filed Mar. 16, 2010, expired, all of which are incorporatedherein by reference in their entirety and made part of the present U.S.Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government support under Contract No.2009*0674524*000 awarded by the Central Intelligence Agency. TheGovernment has certain rights in the invention.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computing systems and moreparticularly to data storage solutions within such computing systems.

Description of Related Art

Computers are known to communicate, process, and store data. Suchcomputers range from wireless smart phones to data centers that supportmillions of web searches, stock trades, or on-line purchases every day.In general, a computing system generates data and/or manipulates datafrom one form into another. For instance, an image sensor of thecomputing system generates raw picture data and, using an imagecompression program (e.g., JPEG, MPEG, etc.), the computing systemmanipulates the raw picture data into a standardized compressed image.

With continued advances in processing speed and communication speed,computers are capable of processing real time multimedia data forapplications ranging from simple voice communications to streaming highdefinition video. As such, general-purpose information appliances arereplacing purpose-built communications devices (e.g., a telephone). Forexample, smart phones can support telephony communications but they arealso capable of text messaging and accessing the internet to performfunctions including email, web browsing, remote applications access, andmedia communications (e.g., telephony voice, image transfer, musicfiles, video files, real time video streaming. etc.).

Each type of computer is constructed and operates in accordance with oneor more communication, processing, and storage standards. As a result ofstandardization and with advances in technology, more and moreinformation content is being converted into digital formats. Forexample, more digital cameras are now being sold than film cameras, thusproducing more digital pictures. As another example, web-basedprogramming is becoming an alternative to over the air televisionbroadcasts and/or cable broadcasts. As further examples, papers, books,video entertainment, home video, etc. are now being stored digitally,which increases the demand on the storage function of computers.

A typical computer storage system includes one or more memory devicesaligned with the needs of the various operational aspects of thecomputer's processing and communication functions. Generally, theimmediacy of access dictates what type of memory device is used. Forexample, random access memory (RAM) memory can be accessed in any randomorder with a constant response time, thus it is typically used for cachememory and main memory. By contrast, memory device technologies thatrequire physical movement such as magnetic disks, tapes, and opticaldiscs, have a variable response time as the physical movement can takelonger than the data transfer, thus they are typically used forsecondary memory (e.g., hard drive, backup memory, etc.).

A computer's storage system will be compliant with one or more computerstorage standards that include, but are not limited to, network filesystem (NFS), flash file system (FFS), disk file system (DFS), smallcomputer system interface (SCSI), internet small computer systeminterface (iSCSI), file transfer protocol (FTP), and web-baseddistributed authoring and versioning (WebDAV). These standards specifythe data storage format (e.g., files, data objects, data blocks,directories, etc.) and interfacing between the computer's processingfunction and its storage system, which is a primary function of thecomputer's memory controller.

Despite the standardization of the computer and its storage system,memory devices fail; especially commercial grade memory devices thatutilize technologies incorporating physical movement (e.g., a discdrive). For example, it is fairly common for a disc drive to routinelysuffer from bit level corruption and to completely fail after threeyears of use. One solution is to utilize a higher-grade disc drive,which adds significant cost to a computer.

Another solution is to utilize multiple levels of redundant disc drivesto replicate the data into two or more copies. One such redundant driveapproach is called redundant array of independent discs (RAID). In aRAID device, a RAID controller adds parity data to the original databefore storing it across the array. The parity data is calculated fromthe original data such that the failure of a disc will not result in theloss of the original data. For example, RAID 5 uses three discs toprotect data from the failure of a single disc. The parity data, andassociated redundancy overhead data, reduces the storage capacity ofthree independent discs by one third (e.g., n−1=capacity). RAID 6 canrecover from a loss of two discs and requires a minimum of four discswith a storage capacity of n−2.

While RAID addresses the memory device failure issue, it is not withoutits own failure issues that affect its effectiveness, efficiency andsecurity. For instance, as more discs are added to the array, theprobability of a disc failure increases, which increases the demand formaintenance. For example, when a disc fails, it needs to be manuallyreplaced before another disc fails and the data stored in the RAIDdevice is lost. To reduce the risk of data loss, data on a RAID deviceis typically copied on to one or more other RAID devices. While thisaddresses the loss of data issue, it raises a security issue sincemultiple copies of data are available, which increases the chances ofunauthorized access. Further, as the amount of data being stored grows,the overhead of RAID devices becomes a non-trivial efficiency issue.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a computingsystem in accordance with the invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the invention;

FIG. 3 is a schematic block diagram of an embodiment of a distributedstorage processing unit in accordance with the invention;

FIG. 4 is a schematic block diagram of an embodiment of a grid module inaccordance with the invention;

FIG. 5 is a diagram of an example embodiment of error coded data slicecreation in accordance with the invention;

FIG. 6 is a flowchart illustrating an example of storing an encoded dataslice in accordance with the invention;

FIG. 7 is a flowchart illustrating an example of deleting an encodeddata slice in accordance with the invention;

FIG. 8 is an example table illustrating a slice location table inaccordance with the invention;

FIG. 9 is a flowchart illustrating an example of compacting slicestorage in accordance with the invention; and

FIG. 10 is a flowchart illustrating another example of deleting anencoded data slice in accordance with the invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of a computing system 10 thatincludes one or more of a first type of user devices 12, one or more ofa second type of user devices 14, at least one distributed storage (DS)processing unit 16, at least one DS managing unit 18, at least onestorage integrity processing unit 20, and a distributed storage network(DSN) memory 22 coupled via a network 24. The network 24 may include oneor more wireless and/or wire lined communication systems; one or moreprivate intranet systems and/or public internet systems; and/or one ormore local area networks (LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of distributed storage (DS) units36 for storing data of the system. Each of the DS units 36 includes aprocessing module and memory and may be located at a geographicallydifferent site than the other DS units (e.g., one in Chicago, one inMilwaukee, etc.). The processing module may be a single processingdevice or a plurality of processing devices. Such a processing devicemay be a microprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module may have an associatedmemory and/or memory element, which may be a single memory device, aplurality of memory devices, and/or embedded circuitry of the processingmodule. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module includes morethan one processing device, the processing devices may be centrallylocated (e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that when the processing module implements one or more ofits functions via a state machine, analog circuitry, digital circuitry,and/or logic circuitry, the memory and/or memory element storing thecorresponding operational instructions may be embedded within, orexternal to, the circuitry comprising the state machine, analogcircuitry, digital circuitry, and/or logic circuitry. Still further notethat, the memory element stores, and the processing module executes,hard coded and/or operational instructions corresponding to at leastsome of the steps and/or functions illustrated in FIGS. 1-10.

Each of the user devices 12-14, the DS processing unit 16, the DSmanaging unit 18, and the storage integrity processing unit 20 may be aportable computing device (e.g., a social networking device, a gamingdevice, a cell phone, a smart phone, a personal digital assistant, adigital music player, a digital video player, a laptop computer, ahandheld computer, a video game controller, and/or any other portabledevice that includes a computing core) and/or a fixed computing device(e.g., a personal computer, a computer server, a cable set-top box, asatellite receiver, a television set, a printer, a fax machine, homeentertainment equipment, a video game console, and/or any type of homeor office computing equipment). Such a portable or fixed computingdevice includes a computing core 26 and one or more interfaces 30, 32,and/or 33. An embodiment of the computing core 26 will be described withreference to FIG. 2.

With respect to the interfaces, each of the interfaces 30, 32, and 33includes software and/or hardware to support one or more communicationlinks via the network 24 and/or directly. For example, interface 30supports a communication link (wired, wireless, direct, via a LAN, viathe network 24, etc.) between the first type of user device 14 and theDS processing unit 16. As another example, DSN interface 32 supports aplurality of communication links via the network 24 between the DSNmemory 22 and the DS processing unit 16, the first type of user device12, and/or the storage integrity processing unit 20. As yet anotherexample, interface 33 supports a communication link between the DSmanaging unit 18 and any one of the other devices and/or units 12, 14,16, 20, and/or 22 via the network 24.

In general and with respect to data storage, the system 10 supportsthree primary functions: distributed network data storage management,distributed data storage and retrieval, and data storage integrityverification. In accordance with these three primary functions, data canbe distributedly stored in a plurality of physically different locationsand subsequently retrieved in a reliable and secure manner regardless offailures of individual storage devices, failures of network equipment,the duration of storage, the amount of data being stored, attempts athacking the data, etc.

The DS managing unit 18 performs distributed network data storagemanagement functions, which include establishing distributed datastorage parameters, performing network operations, performing networkadministration, and/or performing network maintenance. The DS managingunit 18 establishes the distributed data storage parameters (e.g.,allocation of virtual DSN memory space, distributed storage parameters,security parameters, billing information, user profile information,etc.) for one or more of the user devices 12-14 (e.g., established forindividual devices, established for a user group of devices, establishedfor public access by the user devices, etc.). For example, the DSmanaging unit 18 coordinates the creation of a vault (e.g., a virtualmemory block) within the DSN memory 22 for a user device (for a group ofdevices, or for public access). The DS managing unit 18 also determinesthe distributed data storage parameters for the vault. In particular,the DS managing unit 18 determines a number of slices (e.g., the numberthat a data segment of a data file and/or data block is partitioned intofor distributed storage) and a read threshold value (e.g., the minimumnumber of slices required to reconstruct the data segment).

As another example, the DS managing unit 18 creates and stores, locallyor within the DSN memory 22, user profile information. The user profileinformation includes one or more of authentication information,permissions, and/or the security parameters. The security parameters mayinclude one or more of encryption/decryption scheme, one or moreencryption keys, key generation scheme, and data encoding/decodingscheme.

As yet another example, the DS managing unit 18 creates billinginformation for a particular user, user group, vault access, publicvault access, etc. For instance, the DS managing unit 18 tracks thenumber of times a user accesses a private vault and/or public vaults,which can be used to generate a per-access bill. In another instance,the DS managing unit 18 tracks the amount of data stored and/orretrieved by a user device and/or a user group, which can be used togenerate a per-data-amount bill.

The DS managing unit 18 also performs network operations, networkadministration, and/or network maintenance. As at least part ofperforming the network operations and/or administration, the DS managingunit 18 monitors performance of the devices and/or units of the system10 for potential failures, determines the devices' and/or units'activation status, determines the devices' and/or units' loading, andany other system level operation that affects the performance level ofthe system 10. For example, the DS managing unit 18 receives andaggregates network management alarms, alerts, errors, statusinformation, performance information, and messages from the devices12-14 and/or the units 16, 20, 22. For example, the DS managing unit 18receives a simple network management protocol (SNMP) message regardingthe status of the DS processing unit 16.

The DS managing unit 18 performs the network maintenance by identifyingequipment within the system 10 that needs replacing, upgrading,repairing, and/or expanding. For example, the DS managing unit 18determines that the DSN memory 22 needs more DS units 36 or that one ormore of the DS units 36 needs updating.

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has a data file 38 and/or data block 40 tostore in the DSN memory 22, it sends the data file 38 and/or data block40 to the DS processing unit 16 via its interface 30. As will bedescribed in greater detail with reference to FIG. 2, the interface 30functions to mimic a conventional operating system (OS) file systeminterface (e.g., network file system (NFS), flash file system (FFS),disk file system (DFS), file transfer protocol (FTP), web-baseddistributed authoring and versioning (WebDAV), etc.) and/or a blockmemory interface (e.g., small computer system interface (SCSI), internetsmall computer system interface (iSCSI), etc.). In addition, theinterface 30 may attach a user identification code (ID) to the data file38 and/or data block 40.

The DS processing unit 16 receives the data file 38 and/or data block 40via its interface 30 and performs a distributed storage (DS) process 34thereon (e.g., an error coding dispersal storage function). The DSprocessing 34 begins by partitioning the data file 38 and/or data block40 into one or more data segments, which is represented as Y datasegments. For example, the DS processing 34 may partition the data file38 and/or data block 40 into a fixed byte size segment (e.g., 2¹ to2^(n) bytes, where n=>2) or a variable byte size (e.g., change byte sizefrom segment to segment, or from groups of segments to groups ofsegments, etc.).

For each of the Y data segments, the DS processing 34 error encodes(e.g., forward error correction (FEC), information dispersal algorithm,or error correction coding) and slices (or slices then error encodes)the data segment into a plurality of error coded (EC) data slices 42-48,which is represented as X slices per data segment. The number of slices(X) per segment, which corresponds to a number of pillars n, is set inaccordance with the distributed data storage parameters and the errorcoding scheme. For example, if a Reed-Solomon (or other FEC scheme) isused in an n/k system, then a data segment is divided into n slices,where k number of slices is needed to reconstruct the original data(i.e., k is the threshold). As a few specific examples, the n/k factormay be 5/3; 6/4; 8/6; 8/5; 16/10.

For each EC slice 42-48, the DS processing unit 16 creates a uniqueslice name and appends it to the corresponding EC slice 42-48. The slicename includes universal DSN memory addressing routing information (e.g.,virtual memory addresses in the DSN memory 22) and user-specificinformation (e.g., user ID, file name, data block identifier, etc.).

The DS processing unit 16 transmits the plurality of EC slices 42-48 toa plurality of DS units 36 of the DSN memory 22 via the DSN interface 32and the network 24. The DSN interface 32 formats each of the slices fortransmission via the network 24. For example, the DSN interface 32 mayutilize an internet protocol (e.g., TCP/IP, etc.) to packetize the ECslices 42-48 for transmission via the network 24.

The number of DS units 36 receiving the EC slices 42-48 is dependent onthe distributed data storage parameters established by the DS managingunit 18. For example, the DS managing unit 18 may indicate that eachslice is to be stored in a different DS unit 36. As another example, theDS managing unit 18 may indicate that like slice numbers of differentdata segments are to be stored in the same DS unit 36. For example, thefirst slice of each of the data segments is to be stored in a first DSunit 36, the second slice of each of the data segments is to be storedin a second DS unit 36, etc. In this manner, the data is encoded anddistributedly stored at physically diverse locations to improve datastorage integrity and security. Further examples of encoding the datasegments will be provided with reference to one or more of FIGS. 2-10.

Each DS unit 36 that receives an EC slice 42-48 for storage translatesthe virtual DSN memory address of the slice into a local physicaladdress for storage. Accordingly, each DS unit 36 maintains a virtual tophysical memory mapping to assist in the storage and retrieval of data.

The first type of user device 12 performs a similar function to storedata in the DSN memory 22 with the exception that it includes the DSprocessing. As such, the device 12 encodes and slices the data fileand/or data block it has to store. The device then transmits the slices11 to the DSN memory via its DSN interface 32 and the network 24.

For a second type of user device 14 to retrieve a data file or datablock from memory, it issues a read command via its interface 30 to theDS processing unit 16. The DS processing unit 16 performs the DSprocessing 34 to identify the DS units 36 storing the slices of the datafile and/or data block based on the read command. The DS processing unit16 may also communicate with the DS managing unit 18 to verify that theuser device 14 is authorized to access the requested data.

Assuming that the user device is authorized to access the requesteddata, the DS processing unit 16 issues slice read commands to at least athreshold number of the DS units 36 storing the requested data (e.g., toat least 10 DS units for a 16/10 error coding scheme). Each of the DSunits 36 receiving the slice read command, verifies the command,accesses its virtual to physical memory mapping, retrieves the requestedslice, or slices, and transmits it to the DS processing unit 16.

Once the DS processing unit 16 has received a read threshold number ofslices for a data segment, it performs an error decoding function andde-slicing to reconstruct the data segment. When Y number of datasegments has been reconstructed, the DS processing unit 16 provides thedata file 38 and/or data block 40 to the user device 14. Note that thefirst type of user device 12 performs a similar process to retrieve adata file and/or data block.

The storage integrity processing unit 20 performs the third primaryfunction of data storage integrity verification. In general, the storageintegrity processing unit 20 periodically retrieves slices 45, and/orslice names, of a data file or data block of a user device to verifythat one or more slices have not been corrupted or lost (e.g., the DSunit failed). The retrieval process mimics the read process previouslydescribed.

If the storage integrity processing unit 20 determines that one or moreslices is corrupted or lost, it rebuilds the corrupted or lost slice(s)in accordance with the error coding scheme. The storage integrityprocessing unit 20 stores the rebuilt slice, or slices, in theappropriate DS unit(s) 36 in a manner that mimics the write processpreviously described.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (10)controller 56, a peripheral component interconnect (PCI) interface 58,an 10 interface 60, at least one 10 device interface module 62, a readonly memory (ROM) basic input output system (BIOS) 64, and one or morememory interface modules. The memory interface module(s) includes one ormore of a universal serial bus (USB) interface module 66, a host busadapter (HBA) interface module 68, a network interface module 70, aflash interface module 72, a hard drive interface module 74, and a DSNinterface module 76. Note the DSN interface module 76 and/or the networkinterface module 70 may function as the interface 30 of the user device14 of FIG. 1. Further note that the IO device interface module 62 and/orthe memory interface modules may be collectively or individuallyreferred to as IO ports.

The processing module 50 may be a single processing device or aplurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module 50 may have anassociated memory and/or memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry of theprocessing module 50. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module 50includes more than one processing device, the processing devices may becentrally located (e.g., directly coupled together via a wired and/orwireless bus structure) or may be distributedly located (e.g., cloudcomputing via indirect coupling via a local area network and/or a widearea network). Further note that when the processing module 50implements one or more of its functions via a state machine, analogcircuitry, digital circuitry, and/or logic circuitry, the memory and/ormemory element storing the corresponding operational instructions may beembedded within, or external to, the circuitry comprising the statemachine, analog circuitry, digital circuitry, and/or logic circuitry.Still further note that, the memory element stores, and the processingmodule 50 executes, hard coded and/or operational instructionscorresponding to at least some of the steps and/or functions illustratedin FIGS. 1-10.

FIG. 3 is a schematic block diagram of an embodiment of a dispersedstorage (DS) processing module 34 of user device 12 and/or of the DSprocessing unit 16. The DS processing module 34 includes a gatewaymodule 78, an access module 80, a grid module 82, and a storage module84. The DS processing module 34 may also include an interface 30 and theDSnet interface 32 or the interfaces 68 and/or 70 may be part of userdevice 12 or of the DS processing unit 16. The DS processing module 34may further include a bypass/feedback path between the storage module 84to the gateway module 78. Note that the modules 78-84 of the DSprocessing module 34 may be in a single unit or distributed acrossmultiple units.

In an example of storing data, the gateway module 78 receives anincoming data object that includes a user ID field 86, an object namefield 88, and the data object field 40 and may also receivecorresponding information that includes a process identifier (e.g., aninternal process/application ID), metadata, a file system directory, ablock number, a transaction message, a user device identity (ID), a dataobject identifier, a source name, and/or user information. The gatewaymodule 78 authenticates the user associated with the data object byverifying the user ID 86 with the DS managing unit 18 and/or anotherauthenticating unit.

When the user is authenticated, the gateway module 78 obtains userinformation from the management unit 18, the user device, and/or theother authenticating unit. The user information includes a vaultidentifier, operational parameters, and user attributes (e.g., userdata, billing information, etc.). A vault identifier identifies a vault,which is a virtual memory space that maps to a set of DS storage units36. For example, vault 1 (i.e., user 1's DSN memory space) includeseight DS storage units (X=8 wide) and vault 2 (i.e., user 2's DSN memoryspace) includes sixteen DS storage units (X=16 wide). The operationalparameters may include an error coding algorithm, the width n (number ofpillars X or slices per segment for this vault), a read threshold T, awrite threshold, an encryption algorithm, a slicing parameter, acompression algorithm, an integrity check method, caching settings,parallelism settings, and/or other parameters that may be used to accessthe DSN memory layer.

The gateway module 78 uses the user information to assign a source name35 to the data. For instance, the gateway module 78 determines thesource name 35 of the data object 40 based on the vault identifier andthe data object. For example, the source name may contain a fileidentifier (ID), a vault generation number, a reserved field, and avault identifier (ID). As another example, the gateway module 78 maygenerate the file ID based on a hash function of the data object 40.Note that the gateway module 78 may also perform message conversion,protocol conversion, electrical conversion, optical conversion, accesscontrol, user identification, user information retrieval, trafficmonitoring, statistics generation, configuration, management, and/orsource name determination.

The access module 80 receives the data object 40 and creates a series ofdata segments 1 through Y 90-92 in accordance with a data storageprotocol (e.g., file storage system, a block storage system, and/or anaggregated block storage system). The number of segments Y may be chosenor randomly assigned based on a selected segment size and the size ofthe data object. For example, if the number of segments is chosen to bea fixed number, then the size of the segments varies as a function ofthe size of the data object. For instance, if the data object is animage file of 4,194,304 eight bit bytes (e.g., 33,554,432 bits) and thenumber of segments Y=131,072, then each segment is 256 bits or 32 bytes.As another example, if segment size is fixed, then the number ofsegments Y varies based on the size of data object. For instance, if thedata object is an image file of 4,194,304 bytes and the fixed size ofeach segment is 4,096 bytes, then the number of segments Y=1,024. Notethat each segment is associated with the same source name.

The grid module 82 receives the data segments and may manipulate (e.g.,compression, encryption, cyclic redundancy check (CRC), etc.) each ofthe data segments before performing an error coding function of theerror coding dispersal storage function to produce a pre-manipulateddata segment. After manipulating a data segment, if applicable, the gridmodule 82 error encodes (e.g., Reed-Solomon, Convolution encoding,Trellis encoding, etc.) the data segment or manipulated data segmentinto X error coded data slices 42-44.

The value X, or the number of pillars (e.g., X=16), is chosen as aparameter of the error coding dispersal storage function. Otherparameters of the error coding dispersal function include a readthreshold T, a write threshold W, etc. The read threshold (e.g., T=10,when X=16) corresponds to the minimum number of error-free error codeddata slices required to reconstruct the data segment. In other words,the DS processing module 34 can compensate for X−T (e.g., 16−10=6)missing error coded data slices per data segment. The write threshold Wcorresponds to a minimum number of DS storage units that acknowledgeproper storage of their respective data slices before the DS processingmodule indicates proper storage of the encoded data segment. Note thatthe write threshold is greater than or equal to the read threshold for agiven number of pillars (X).

For each data slice of a data segment, the grid module 82 generates aunique slice name 37 and attaches it thereto. The slice name 37 includesa universal routing information field and a vault specific field and maybe 48 bytes (e.g., 24 bytes for each of the universal routinginformation field and the vault specific field). As illustrated, theuniversal routing information field includes a slice index, a vault ID,a vault generation, and a reserved field. The slice index is based onthe pillar number and the vault ID and, as such, is unique for eachpillar (e.g., slices of the same pillar for the same vault for anysegment will share the same slice index). The vault specific fieldincludes a data name, which includes a file ID and a segment number(e.g., a sequential numbering of data segments 1−Y of a simple dataobject or a data block number).

Prior to outputting the error coded data slices of a data segment, thegrid module may perform post-slice manipulation on the slices. Ifenabled, the manipulation includes slice level compression, encryption,CRC, addressing, tagging, and/or other manipulation to improve theeffectiveness of the computing system.

When the error coded data slices of a data segment are ready to beoutputted, the grid module 82 determines which of the DS storage units36 will store the EC data slices based on a dispersed storage memorymapping associated with the user's vault and/or DS storage unitattributes. The DS storage unit attributes may include availability,self-selection, performance history, link speed, link latency,ownership, available DSN memory, domain, cost, a prioritization scheme,a centralized selection message from another source, a lookup table,data ownership, and/or any other factor to optimize the operation of thecomputing system. Note that the number of DS storage units 36 is equalto or greater than the number of pillars (e.g., X) so that no more thanone error coded data slice of the same data segment is stored on thesame DS storage unit 36. Further note that EC data slices of the samepillar number but of different segments (e.g., EC data slice 1 of datasegment 1 and EC data slice 1 of data segment 2) may be stored on thesame or different DS storage units 36.

The storage module 84 performs an integrity check on the outboundencoded data slices and, when successful, identifies a plurality of DSstorage units based on information provided by the grid module 82. Thestorage module 84 then outputs the encoded data slices 1 through X ofeach segment 1 through Y to the DS storage units 36. Each of the DSstorage units 36 stores its EC data slice(s) and maintains a localvirtual DSN address to physical location table to convert the virtualDSN address of the EC data slice(s) into physical storage addresses.

In an example of a read operation, the user device 12 and/or 14 sends aread request to the DS processing unit 14, which authenticates therequest. When the request is authentic, the DS processing unit 14 sendsa read message to each of the DS storage units 36 storing slices of thedata object being read. The slices are received via the DSnet interface32 and processed by the storage module 84, which performs a parity checkand provides the slices to the grid module 82 when the parity check wassuccessful. The grid module 82 decodes the slices in accordance with theerror coding dispersal storage function to reconstruct the data segment.The access module 80 reconstructs the data object from the data segmentsand the gateway module 78 formats the data object for transmission tothe user device.

FIG. 4 is a schematic block diagram of an embodiment of a grid module 82that includes a control unit 73, a pre-slice manipulator 75, an encoder77, a slicer 79, a post-slice manipulator 81, a pre-slice de-manipulator83, a decoder 85, a de-slicer 87, and/or a post-slice de-manipulator 89.Note that the control unit 73 may be partially or completely external tothe grid module 82. For example, the control unit 73 may be part of thecomputing core at a remote location, part of a user device, part of theDS managing unit 18, or distributed amongst one or more DS storageunits.

In an example of a write operation, the pre-slice manipulator 75receives a data segment 90-92 and a write instruction from an authorizeduser device. The pre-slice manipulator 75 determines if pre-manipulationof the data segment 90-92 is required and, if so, what type. Thepre-slice manipulator 75 may make the determination independently orbased on instructions from the control unit 73, where the determinationis based on a computing system-wide predetermination, a table lookup,vault parameters associated with the user identification, the type ofdata, security requirements, available DSN memory, performancerequirements, and/or other metadata.

Once a positive determination is made, the pre-slice manipulator 75manipulates the data segment 90-92 in accordance with the type ofmanipulation. For example, the type of manipulation may be compression(e.g., Lempel-Ziv-Welch, Huffman, Golomb, fractal, wavelet, etc.),signatures (e.g., Digital Signature Algorithm (DSA), Elliptic Curve DSA,Secure Hash Algorithm, etc.), watermarking, tagging, encryption (e.g.,Data Encryption Standard, Advanced Encryption Standard, etc.), addingmetadata (e.g., time/date stamping, user information, file type, etc.),cyclic redundancy check (e.g., CRC32), and/or other data manipulationsto produce the pre-manipulated data segment.

The encoder 77 encodes the pre-manipulated data segment 92 using aforward error correction (FEC) encoder (and/or other type of erasurecoding and/or error coding) to produce an encoded data segment 94. Theencoder 77 determines which forward error correction algorithm to usebased on a predetermination associated with the user's vault, a timebased algorithm, user direction, DS managing unit direction, controlunit direction, as a function of the data type, as a function of thedata segment 92 metadata, and/or any other factor to determine algorithmtype. The forward error correction algorithm may be Golay,Multidimensional parity, Reed-Solomon, Hamming, Bose Ray ChauduriHocquenghem (BCH), Cauchy-Reed-Solomon, or any other FEC encoder. Notethat the encoder 77 may use a different encoding algorithm for each datasegment 92, the same encoding algorithm for the data segments 92 of adata object, or a combination thereof.

The encoded data segment 94 is of greater size than the data segment 92by the overhead rate of the encoding algorithm by a factor of X/T, whereX is the width or number of slices, and T is the read threshold. In thisregard, the corresponding decoding process can accommodate at most X-Tmissing EC data slices and still recreate the data segment 92. Forexample, if X=16 and T=10, then the data segment 92 will be recoverableas long as 10 or more EC data slices per segment are not corrupted.

The slicer 79 transforms the encoded data segment 94 into EC data slicesin accordance with the slicing parameter from the vault for this userand/or data segment 92. For example, if the slicing parameter is X=16,then the slicer 79 slices each encoded data segment 94 into 16 encodedslices.

The post-slice manipulator 81 performs, if enabled, post-manipulation onthe encoded slices to produce the EC data slices. If enabled, thepost-slice manipulator 81 determines the type of post-manipulation,which may be based on a computing system-wide predetermination,parameters in the vault for this user, a table lookup, the useridentification, the type of data, security requirements, available DSNmemory, performance requirements, control unit directed, and/or othermetadata. Note that the type of post-slice manipulation may includeslice level compression, signatures, encryption, CRC, addressing,watermarking, tagging, adding metadata, and/or other manipulation toimprove the effectiveness of the computing system.

In an example of a read operation, the post-slice de-manipulator 89receives at least a read threshold number of EC data slices and performsthe inverse function of the post-slice manipulator 81 to produce aplurality of encoded slices. The de-slicer 87 de-slices the encodedslices to produce an encoded data segment 94. The decoder 85 performsthe inverse function of the encoder 77 to recapture the data segment90-92. The pre-slice de-manipulator 83 performs the inverse function ofthe pre-slice manipulator 75 to recapture the data segment 90-92.

FIG. 5 is a diagram of an example of slicing an encoded data segment 94by the slicer 79. In this example, the encoded data segment 94 includesthirty-two bits, but may include more or less bits. The slicer 79disperses the bits of the encoded data segment 94 across the EC dataslices in a pattern as shown. As such, each EC data slice does notinclude consecutive bits of the data segment 94 reducing the impact ofconsecutive bit failures on data recovery. For example, if EC data slice2 (which includes bits 1, 5, 9, 13, 17, 25, and 29) is unavailable(e.g., lost, inaccessible, or corrupted), the data segment can bereconstructed from the other EC data slices (e.g., 1, 3 and 4 for a readthreshold of 3 and a width of 4).

FIG. 6 is a flowchart illustrating an example of storing an encoded dataslice. The method begins with step 110 where a processing module (e.g.,a dispersed storage (DS) unit) receives an encoded data slice forstorage in memory that is organized as a plurality of log files. Themethod continues at step 112 where the processing module identifies alog file based on information regarding the encoded data slice toproduce an identified log file, wherein the identified log file isstoring at least one other encoded data slice (e.g., the other encodedslice may be associated with a data file that is not associated with theencoded data slice). The information of the encoded data slice includesat least one of a data identifier (ID) of a file associated with theencoded data slice, a user ID associated with the encoded data slice,and an indication of the log file contained in a message accompanyingthe encoded data slice.

A log file may represent a portion of a file and may be utilized tostore one or more slices. For example, a log file includes a rangewithin a file wherein the range is less than the size of the file. Asanother example, a log file includes an entire file. Such identifying ofthe log file may be based on one or more of a most recently compactedlog file, a log file with the most available space, and log file withavailable space greater than the threshold, a lookup, determination, adate identifier (ID), a user ID, and a message. For example, theprocessing module selects log file 5F8 when the processing moduledetermines that log file 5F8 has more available space than other logfiles.

The method continues at step 114 where the processing module comparesstorage parameters of the identified log file with desired storageparameters associated with the encoded data slice. The processing modulemay determine the desired storage parameters based on one or more of theinformation of the encoded data slice, a lookup, a message, and apredetermination. The comparing of the storage parameters of theidentified log file with the desired storage parameters being favorablewhen the log file is identified as a most recently compacted log file,the log file is identified as having a favorable amount of availablestorage space, the log file is identified in a slice location tablelookup, the log file is predetermined, or the log file is identifiedbased on a slice name associated with the encoded data slice.

The comparing of the storage parameters of the identified log file withthe desired storage parameters being unfavorable when the identified logfile includes a number of storage gaps that compares unfavorably to agap threshold (e.g., too many gaps of free space, from deleted slices,between actively utilized areas). The comparing of the storageparameters of the identified log file with the desired storageparameters being further unfavorable when a storage balance between theidentified log file and the second log file compares unfavorably to astorage balance threshold. For example, the processing module indicatesan unfavorable comparison when there are twice as many storage gapsassociated with the identified log file as compared to the second logfile. The comparing of the storage parameters of the identified log filewith the desired storage parameters being unfavorable further when astorage capacity of the identified log file compares unfavorably to astorage threshold.

The method branches to step 122 when the processing module compares thestorage parameters of the identified log file with desired storageparameters as unfavorable, The method continues to step 116 when theprocessing module compares the storage parameters of the identified logfile with desired storage parameters as favorable, The method continuesat step 116 where the processing module identifies a log file offset foran available storage location of the identified log file when thestorage parameters of the identified log file compare favorably with thedesired storage parameters. The log file offset indicates a number ofbytes from the beginning of the log file to the storage location (e.g.,for storing the encoded data slice within the log file). The identifyingmay be based on one or more of a slice location table lookup, summing alast stored encoded data slice size with a storage location associatedwith an encoded data slice that was a last stored encoded data slice inthe log file, a sum of all encoded data slice sizes previously stored inthe log file, an available space indicator, a beginning of the log fileof the log file identifier (ID), an end of the log file of the log fileID, an encoded data slice size indicator, and a last utilized log fileoffset.

The method continues at step 118 where the processing module stores theencoded data slice in the identified log file based on log file offset.For example, the processing module stores the encoded data slice at anaddress within the log file that is a log file number of bytes from astarting address of the log file. The method continues at step 120 wherethe processing module updates a slice location table to include storageof the encoded data slice in the identified log file (e.g., storing aslice name of the encoded data slice, a log file ID, the log fileoffset).

The method continues at step 122 where the processing module attempts toidentify a second log file based on an alternate log file storageprotocol when the storage parameters of the identified log file compareunfavorably with the desired storage parameters. Such an alternate logfile storage protocol attempts to identify another log file that meetsthe desired storage parameters. The method branches to step 126 when theprocessing module identifies the second log file. The method continuesto step 124 when the processing module does not identify the second logfile. The method continues at step 124 where the processing modulestores the encoded data slice in the second log file when the second logfile is identified. The method continues at step 126 where theprocessing module creates another log file when the second log file isnot identified. The method continues at step 128 where the processingmodule stores the encoded data slice in the other log file.

FIG. 7 is a flowchart illustrating an example of deleting an encodeddata slice, that includes similar steps to FIG. 6. The method beginswith step 130 where a processing module (e.g., a dispersed storage (DS)unit) receives a delete encoded data slice message, wherein the messageincludes a slice name. For example, the processing module receives afinalize request message that includes a slice name and an empty encodeddata slice field to receive the delete encoded data slice message. Themethod continues with steps 112 and 116 of FIG. 6 where the processingmodule identifies a log file based on the slice name to produce anidentified log file and identifies a log file offset based on the slicename. The method continues with step 132 where the processing moduleupdates a slice location table to indicate that storage space is deletedat the log file offset within the log file (e.g., at least an amount ofstorage space equivalent to a slice size of the encoded data slice isdeleted and available for potential storing of another encoded dataslice).

FIG. 8 is an example table illustrating a slice location table 134. Theslice location table 134 includes a slice identifier field 136, a sizefield 138, and a location field 140. The size field 138 includes aplurality of size entries corresponding to a plurality of stored slices,wherein each size entry may be utilized to indicate a size (e.g., numberof bytes) of a corresponding stored slice or to identify a size of anavailable portion of a corresponding log file. The slice identifierfield 136 includes a slice name field 142 and a revision identifierfield 144 to indicate slice names and revisions that correspond to theplurality of stored slices. The location field 140 includes a log fileidentifier field 146 and an offset field 148. The log file identifierfield 146 includes log file identifier entries representing whereencoded data slices are stored corresponding to slice name entries andthe offset field 148 includes offset entries corresponding to where theencoded data slices are stored within log files.

In an example, slice name 1AC revision 1 of size 100 bytes is stored inlog file 5F8 at offset 200. As another example, slice name 7D1 revision1 of size 200 is stored in log file 5F8 at offset 1400. The slicelocation table may be utilized to select log file identifier 5F8 tostore a new slice at offset 1600 that is of size 200 or smaller based onan entry in the slice location table that indicates that a 200 byteportion of log file 5F8 is available (e.g., free) at offset 1600.

FIG. 9 is a flowchart illustrating an example of compacting slicestorage. The method begins with step 150 where a processing module(e.g., a dispersed storage (DS) processing unit) identifies a firststorage space zone that includes a plurality of deleted encoded dataslices and a plurality of active encoded data slices. The processingmodule identifies the first storage space zone in a memory that isorganized as a plurality of log files. Alternatively, a log file mayinclude one or more storage space zones. The processing moduleidentifies one or more of the plurality of log files associated with thefirst storage space zone.

The method continues at step 152 where the processing module determinesto compact the first storage space zone based on a function of theplurality of deleted encoded data slices and the plurality of activeencoded data slices. Alternatively, the processing module determines tocompact the first storage space zone based on a function of theplurality of deleted encoded data slices, the plurality of activeencoded data slices, and available storage in the first storage spacezone. The function includes determining a total storage valuecorresponding to total storage space of the first storage space zone,determining a deleted slice value corresponding to storage spaceoccupied by the plurality of deleted encoded data slices, determining anactive slice value corresponding to storage space occupied by theplurality of active encoded data slices, determining an availablestorage value corresponding to available storage space of the firststorage space zone, determining a compacting value based on the totalstorage value, the deleted slice value, the active slice value, and theavailable storage value, and interpreting the compacting value to whento compact the first storage space zone.

In an example of operation, the processing module determines to compactthe first storage space zone when a number of the deleted encoded dataslices is greater than a number of the plurality of active encoded dataslices when the function is determining the deleted slice valuecorresponding to storage space occupied by the plurality of deletedencoded data slices and determining the active slice value correspondingto storage space occupied by the plurality of active encoded dataslices. As another example, a probability that a compaction operationwill be selected instead of a write operation is calculated inaccordance with a function of: p=(D/(D+W)) ̂(f*E/T), wherein f is afactor that can be used to increase the steepness of the curve, T=totalphysical storage available, W=is written active encoded data slices,D=deleted encoded data slices, and E=empty available space available fornew data to be written. Utilizing such a function may result incompaction probability going to 100% as empty space approaches zero andit does so more quickly when a higher proportion of deleted encoded dataslices exists.

The method continues at step 154 where the processing module retrievesthe plurality of active encoded data slices from the first storage spacezone when the first storage space zone is to be compacted. The methodcontinues at step 156 where the processing module identifies a secondstorage space zone. The processing module identifies one or more otherlog files of the plurality of log files associated with the secondstorage space zone. The identifying the second storage space zoneincludes determining data size of the plurality of active encoded dataslices, determining whether the second storage space zone includesavailable and contiguous storage space that is equal to or exceeds thedata size of the plurality of active encoded data slices, and when thesecond storage space zone includes available and contiguous storagespace that is equal to or exceeds the data size of the plurality ofactive encoded data slices, selecting the second storage space zone.

The method continues at step 158 where the processing module stores theplurality of active encoded data slices in the second storage spacezone. Alternatively, the processing module stores the plurality ofdeleted encoded data slices in the second storage space zone when thefirst storage space zone is to be compacted (e.g., when the secondstorage space zone is much larger than the data being transferred). Themethod continues at step 160 where the processing module erases theplurality of deleted encoded data slices and the plurality of activeencoded data slices from the first storage space zone. The erasing thefirst storage space zone includes updating a slice location table toremove association of the plurality of deleted encoded data slices andthe plurality of active encoded data slices within the first storagespace zone (e.g., deleting from first zone, thus compacting) andupdating the slice location table to indicate that the plurality ofactive encoded data slices is stored in the second storage space zone.

FIG. 10 is a flowchart illustrating another example of deleting anencoded data slice. The method begins with step 162 where a processingmodule (e.g., a dispersed storage (DS) processing unit) receives amessage to delete one of the plurality of active encoded data slices(e.g., receive a finalize request message that includes a slice name andan empty encoded data slice field). The method continues at step 164where the processing module identifies storage space of the firststorage space zone storing the one of the plurality of active encodeddata slices. The method continues at step 166 where the processingmodule updates a slice location table to indicate that the one of theplurality of active encoded data slices is deleted from the storagespace to produce an updated plurality of deleted encoded data slices andan updated plurality of active encoded data slices.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “module”,“processing circuit”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may have anassociated memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of the processing module, module, processing circuit, and/orprocessing unit. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc. that may usethe same or different reference numbers and, as such, the functions,steps, modules, etc. may be the same or similar functions, steps,modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a functional block that isimplemented via hardware to perform one or module functions such as theprocessing of one or more input signals to produce one or more outputsignals. The hardware that implements the module may itself operate inconjunction software, and/or firmware. As used herein, a module maycontain one or more sub-modules that themselves are modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by a storage unit of adispersed storage network (DSN), the method comprises: receiving a firstencoded data slice for storage in memory that is organized as aplurality of log files, wherein the first encoded data slice includes afirst DSN virtual address and first size information, wherein a log fileof the plurality of log files corresponds to a block of the memory thatincludes a plurality of data blocks, wherein the plurality of datablocks is addressable based on a log file identifier of the log file andoffset values, wherein a first data block of the plurality of datablocks includes an address of the log file identifier and a first offsetvalue; identifying a first log file of the plurality of log files forstoring the first encoded data slice based on one or more of: the firstDSN virtual address and the first size information, wherein the firstlog file is currently storing a second encoded data slice having asecond DSN virtual address, wherein the second DSN virtual address isrelated to the first DSN virtual address; comparing storage parametersof the first log file with desired storage parameters associated withthe first encoded data slice; and when the storage parameters of theidentified log file compare unfavorably with the desired storageparameters: attempting to identify a second log file of the plurality oflog files based on an alternate log file storage protocol; when thesecond log file is identified, storing the first encoded data slice inone or more data blocks of the second log file; and updating a slicelocation table to include storage of the first encoded data slice in theone or more data blocks of the second log file, wherein the firstencoded data slice is identified in the slice location table based onthe first DSN virtual address, the log file identifier of the second logfile, and an offset value corresponding to the one or more data blocksof the second log file.
 2. The method of claim 1, wherein the storageparameters of the first log file comprise one or more of: a number ofstorage gaps within the first log file; compacting status of the firstlog file; available storage space of the first log file; and storagebalance indicator that indicates storage balance between the first andsecond log files.
 3. The method of claim 1, wherein the identifying afirst log file comprises one or more of: identifying the first log filebased on the slice location table based on the first DSN virtual addressbeing related to the second DSN virtual address; identifying the firstlog file based on a predetermined selection process for storing encodeddata slices in the plurality of log files; and identifying the first logfile as being a most recently compacted log file, wherein compacting ofthe first log file includes removing storage gaps.
 4. The method ofclaim 1 further comprises: when the storage parameters of the identifiedlog file compare favorably with the desired storage parameters: storingthe first encoded data slice in one or more data blocks of the first logfile; and updating the slice location table to include storage of thefirst encoded data slice in the one or more data blocks of the first logfile.
 5. The method of claim 1, wherein the desired storage parametersassociated with the first encoded data slice comprises one or more of:storage in a log file of the plurality of log files in which a relatedencoded data slice is stored, wherein a related encoded data slice is ofa different set of encoded data slices than the first encoded data slicebut is of the same plurality of sets of encoded data slices, wherein adata object is dispersed storage error encoded into the plurality ofsets of encoded data slices; and the size information of the firstencoded data slice corresponds to data block size of a log file of theplurality of log files.
 6. A computer readable memory device comprises:a first memory section that stores operational instructions that, whenexecuted by a storage unit of a dispersed storage network (DSN), causesthe storage unit to: receive a first encoded data slice for storage inmemory that is organized as a plurality of log files, wherein the firstencoded data slice includes a first DSN virtual address and first sizeinformation, wherein a log file of the plurality of log filescorresponds to a block of the memory that includes a plurality of datablocks, wherein the plurality of data blocks is addressable based on alog file identifier of the log file and offset values, wherein a firstdata block of the plurality of data blocks includes an address of thelog file identifier and a first offset value; a second memory sectionthat stores operational instructions that, when executed by the storageunit, causes the storage unit to: identify a first log file of theplurality of log files for storing the first encoded data slice based onone or more of: the first DSN virtual address and the first sizeinformation, wherein the first log file is currently storing a secondencoded data slice having a second DSN virtual address, wherein thesecond DSN virtual address is related to the first DSN virtual address;and a third memory section that stores operational instructions that,when executed by the storage unit, causes the storage unit to: comparestorage parameters of the first log file with desired storage parametersassociated with the first encoded data slice; and when the storageparameters of the identified log file compare unfavorably with thedesired storage parameters: attempt to identify a second log file of theplurality of log files based on an alternate log file storage protocol;when the second log file is identified, store the first encoded dataslice in one or more data blocks of the second log file; and update aslice location table to include storage of the first encoded data slicein the one or more data blocks of the second log file, wherein the firstencoded data slice is identified in the slice location table based onthe first DSN virtual address, the log file identifier of the second logfile, and an offset value corresponding to the one or more data blocksof the second log file.
 7. The computer readable memory device of claim6, wherein the storage parameters of the first log file comprise one ormore of: a number of storage gaps within the first log file; compactingstatus of the first log file; available storage space of the first logfile; and storage balance indicator that indicates storage balancebetween the first and second log files.
 8. The computer readable memorydevice of claim 6, wherein the second memory section further storesoperational instructions that, when executed by the storage unit, causesthe storage unit to identify the first log file by one or more of:identifying the first log file based on the slice location table basedon the first DSN virtual address being related to the second DSN virtualaddress; identifying the first log file based on a predeterminedselection process for storing encoded data slices in the plurality oflog files; and identifying the first log file as being a most recentlycompacted log file, wherein compacting of the first log file includesremoving storage gaps.
 9. The computer readable memory device of claim6, wherein the third memory section further stores operationalinstructions that, when executed by the storage unit, causes the storageunit to: when the storage parameters of the identified log file comparefavorably with the desired storage parameters: store the first encodeddata slice in one or more data blocks of the first log file; and updatethe slice location table to include storage of the first encoded dataslice in the one or more data blocks of the first log file.
 10. Thecomputer readable memory device of claim 6, wherein the desired storageparameters associated with the first encoded data slice comprises one ormore of: storage in a log file of the plurality of log files in which arelated encoded data slice is stored, wherein a related encoded dataslice is of a different set of encoded data slices than the firstencoded data slice but is of the same plurality of sets of encoded dataslices, wherein a data object is dispersed storage error encoded intothe plurality of sets of encoded data slices; and the size informationof the first encoded data slice corresponds to data block size of a logfile of the plurality of log files.